Unlocking translational machinery for antitubercular drug development.

Targeting translational factor proteins (TFPs) presents significant promise for the development of innovative antitubercular drugs. Previous insights from antibiotic binding mechanisms and recently solved 3D crystal structures of Mycobacterium tuberculosis (Mtb) elongation factor thermo unstable-GDP (EF-Tu-GDP), elongation factor thermo stable-EF-Tu (EF-Ts-EF-Tu), and elongation factor G-GDP (EF-G-GDP) have opened up new avenues for the design and development of potent antituberculosis (anti-TB) therapies.

An update on ATP synthase inhibitors: A unique target for drug development in M. tuberculosis.

ATP synthase is a key protein in the oxidative phosphorylation process, as it aids in the effective production of ATP (Adenosine triphosphate) in all life's of kingdoms. ATP synthases have distinctive properties that contribute to efficient ATP synthesis. The ATP synthase of mycobacterium is of special relevance since it has been identified as a target for potential anti-TB molecules, especially Bedaquiline (BDQ). Better knowledge of how mycobacterial ATP synthase functions and its peculiar characteristics will aid in our understanding of bacterial energy metabolism adaptations. Furthermore, identifying and understanding the important distinctions between human ATP synthase and bacterial ATP synthase may provide insight into the design and development of inhibitors that target specific ATP synthase. In recent years, many potential candidates targeting the ATP synthase of mycobacterium have been developed. In this review, we discuss the druggable targets of the Electron transport chain (ETC) and recently identified potent inhibitors (including clinical molecules) from 2015 to 2022 of diverse classes that target ATP synthase of M. tuberculosis.

Targeting the cytochrome bc1 complex for drug development in M. tuberculosis: review.

The terminal oxidases of the oxidative phosphorylation pathway play a significant role in the survival and growth of M. tuberculosis, targeting these components lead to inhibition of M. tuberculosis. Many drug candidates targeting various components of the electron transport chain in M. tuberculosis have recently been discovered. The cytochrome bc1-aa3 supercomplex is one of the most important components of the electron transport chain in M. tuberculosis, and it has emerged as the novel target for several promising candidates. There are two cryo-electron microscopy structures (PDB IDs: 6ADQ and 6HWH) of the cytochrome bc1-aa3 supercomplex that aid in the development of effective and potent inhibitors for M. tuberculosis. In recent years, a number of potential candidates targeting the QcrB subunit of the cytochrome bc1 complex have been developed. In this review, we describe the recently identified inhibitors that target the electron transport chain's terminal oxidase enzyme in M. tuberculosis, specifically the QcrB subunit of the cytochrome bc1 complex.

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic mycobacteria have been a global threat urging the need of new drug discovery and development. However, considering the fact that the new drug discovery and development is commonly lengthy and costly processes, strategic use of the cutting-edge machine learning (ML) algorithms may be very supportive in reducing both the cost and time involved. Considering the urgency of new drugs for TB, herein, we have attempted to develop predictive ML algorithms-based models useful in the selection of novel potential small molecules for subsequent in vitro validation. For this purpose, we used the GlaxoSmithKline (GSK) TCAMS TB dataset comprising a total of 776 hits that were made publicly available to the wider scientific community through the ChEMBL Neglected Tropical Diseases (ChEMBL-NTD) database. After exploring the different ML classifiers, viz. decision trees (DT), support vector machine (SVM), random forest (RF), Bernoulli Naive Bayes (BNB), K-nearest neighbors (k-NN), and linear logistic regression (LLR), and ensemble learning models (bagging and Adaboost) for training the model using the GSK dataset, we concluded with three best models, viz. Adaboost decision tree (ABDT), RF classifier, and k-NN models that gave the top prediction results for both the training and test sets. However, during the prediction of the external set of known anti-tubercular compounds/drugs, it was realized that each of these models had some limitations. The ABDT model correctly predicted 22 molecules as actives, while both the RF and k-NN models predicted 18 molecules correctly as actives; a number of molecules were predicted as actives by two of these models, while the third model predicted these compounds as inactives. Therefore, we concluded that while deciding the anti-tubercular potential of a new molecule, one should rely on the use of consensus predictions using these three models; it may lessen the attrition rate during the in vitro validation. We believe that this study may assist the wider anti-tuberculosis research community by providing a platform for predicting small molecules with subsequent validation for drug discovery and development.

Qualitative assessment of compost engendered from municipal solid waste and green waste by indexing method.

The present study aims at quantification of the quality of three varieties of composts made from municipal solid waste, green waste and combined waste by critically evaluating their physicochemical attributes, effect on soil fertility and metal pollution risk. Each waste type was treated with effective micro-organisms to compare the compost quality using Quality Control Indices. The effect of microbial consortia on the wastes was prominent resulting in decreased pH levels and increased electrical conductivity. C/N ratio ranged between 14-24 for waste composts without microbial treatment, and 8-11 for microbial treated wastes. The fertility parameter was observed to be more in microbial treated waste composts. Also, heavy metals concentration in waste compost without effective microbial treatment was higher than the types given EM. Based on the fertility and clean indices, the treated and untreated municipal solid waste and combined waste compost belonged to class RU-1 and class D, respectively. Moreover, compost prepared from treated and untreated green waste belonged to classes B and C respectively. In general, the prepared CW and GW composts have medium to high fertilizing potential and are fit for domestic as well as commercial use. However, MSW compost is not fit for agricultural purposes as it didn't improve soil fertility to a greater extent but can be used as a soil conditioner in limited quantity as it can cause metal toxicity. For this reason, proper segregation of inputs at the start of a composting process is necessary to improve its quality before being put to agricultural use as any unbalanced or unchecked content of mixed waste will affect the overall compost quality.Implications: Significance of the work: The research dealt with different combinations of segregated wastes to analyze the best fit solid waste compost. Experiments were conducted on the actual landfill site area to simulate the conditions for the process. The manuscript provides evidence and other facts advocating the use of composting for waste management and ultimately reducing pollution caused by landfilling. It ought to cause a multiplier effect if the same is to be followed in other parts of the world, and thus working our way toward getting the Smart city project to fruition. The results of the study exhibit the differences in physiochemical nature of various types of composts. A treatment of microbial consortium with restrictions enabled a conducive atmosphere in the colonies to thrive faster and initiate the process of decomposition. We observed that treated samples converted faster into compost as compared to non-treated samples. We also observed the effect of treatment on fertility parameters of prepared compost samples. In general, it was found that the organic carbon and C/N ratio declined while the total nitrogen and total potassium was observed to increase with very little to no change in phosphorous content, with the inoculation of beneficial micro-organisms throughout the composting course. A reduction in the heavy metal levels was observed in samples treated with active micro-organisms. The compost classification into A, B, C, and D classes represents the quality of compost and further use in agricultural land on commercial levels. The quality index values were determined highest for green waste compost (GWC). The municipal solid waste compost (MSWC) exhibited lowest index values. Therefore, based on the quality index values, the utilization of GWC will aid in reutilizing the green waste and in boosting soil fertility and reduce the waste quantity generation rates. It's also necessary to make compost making widespread among the farmers for a sustainable environment. The GWC has been considered as a sustainable option of waste management, being economically and ecologically viable.

Machine learning-enabled predictive modeling to precisely identify the antimicrobial peptides.

The ubiquitous antimicrobial peptides (AMPs), with a broad range of antimicrobial activities, represent a great promise for combating the multi-drug resistant infections. In this study, using a large and diverse set of AMPs (2638) and non-AMPs (3700), we have explored a variety of machine learning classifiers to build in silico models for AMP prediction, including Random Forest (RF), k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Decision Tree (DT), Naive Bayes (NB), Quadratic Discriminant Analysis (QDA), and ensemble learning. Among the various models generated, the RF classifier-based model top-performed in both the internal [Accuracy: 91.40%, Precision: 89.37%, Sensitivity: 90.05%, and Specificity: 92.36%] and external validations [Accuracy: 89.43%, Precision: 88.92%, Sensitivity: 85.21%, and Specificity: 92.43%]. In addition, the RF classifier-based model correctly predicted the known AMPs and non-AMPs; those kept aside as an additional external validation set. The performance assessment revealed three features viz. ChargeD2001, PAAC12 (pseudo amino acid composition), and polarity T13 that are likely to play vital roles in the antimicrobial activity of AMPs. The developed RF-based classification model may further be useful in the design and prediction of the novel potential AMPs.

Effect of environmental toxicants on neuronal functions.

In the last few years, neurodegenerative diseases like Alzheimer's disease (AD) and Parkinson's disease (PD) have attracted attention due to their high prevalence worldwide. Environmental factors may be one of the biggest reasons for these diseases related to neuronal dysfunctions. Most of neuronal disorders are strongly associated with pre- and postnatal exposure to environmental toxins released from industries. Some of the neurotoxic metals such as lead, aluminum, mercury, manganese, cadmium, and arsenic as well as some pesticides and metal-based nanoparticles have been involved in AD and PD due to their ability to produce senile/amyloid plaques and NFTs which are the main feature of these neuronal dysfunctions. Exposure to solvents is also majorly responsible for neurodegenerative disorders. The present review highlights the impact of omnipresent heavy metals with some other neurotoxins on human health and how they give rise to neuronal dysfunctions which in turn causes socio-economic consequences due to increasing pollution worldwide. Graphical abstract.

In vitro bactericidal activity of 3-cinnamoyl-4-hydroxy-6-methyl-2-pyrone (CHP) against drug-susceptible, drug-resistant and drug-tolerant isolates of Mycobacterium tuberculosis.

OBJECTIVES: Tuberculosis (TB) poses a serious global threat to humans. New bactericidal agents that can shorten treatment duration and target drug resistance still remain a top priority in the discovery of anti-TB drugs. The objective of this study was to investigate the bactericidal potential of 3-cinnamoyl-4-hydroxy-6-methyl-2-pyrone (CHP) against drug-susceptible, drug-resistant clinical isolates and drug-tolerant Mycobacterium tuberculosis. METHODS: The minimum bactericidal concentration (MBC) was determined by colony-forming unit (CFU) enumeration. The kill curve analysis was done at different concentrations spanning over 16 days. Drug combination studies with antituberculosis drugs were done to investigate possible synergy. The potential against drug- resistant isolates of M. tuberculosis was done by broth dilution assay. CFU enumeration was done to determine its activity against nutrient-starved drug tolerants, and its feasibility for oral administration was tested by serum inhibitory titre. RESULTS: CHP displayed bactericidal activity with an MBC of 4 µg/mL against M. tuberculosis H37Rv. The kill curve analysis exhibited a biphasic pattern of killing. CHP showed synergy with rifampicin, isoniazid and amikacin but was indifferent towards ethambutol and levofloxacin. CHP retained its full activity against drug-susceptible, monoresistant and multidrug-resistant (MDR) clinical isolates. CHP showed very strong bactericidal activity against nondividing, drug-tolerant M. tuberculosis that on comparison was highly superior to rifampicin. Furthermore, CHP significantly improved the bactericidal activity of rifampicin and isoniazid in a combination study. The serum inhibitory titre in mice indicated its high oral bioavailability. CONCLUSION: Our results show strong bactericidal potential of CHP against M. tuberculosis that warrant its immediate mechanistic, pharmacokinetic and pharmacodynamic studies.

Emerging opportunities of exploiting mycobacterial electron transport chain pathway for drug-resistant tuberculosis drug discovery.

Introduction: Tuberculosis (TB) is a leading infectious disease worldwide whose chemotherapy is challenged by the continued rise of drug resistance. This epidemic urges the need to discover anti-TB drugs with novel modes of action.Areas covered: The mycobacterial electron transport chain (ETC) pathway represents a hub of anti-TB drug targets. Herein, the authors highlight the various targets within the mycobacterial ETC and highlight some of the promising ETC-targeted drugs and clinical candidates that have been discovered or repurposed. Furthermore, recent breakthroughs in the availability of X-ray and/or cryo-EM structures of some targets are discussed, and various opportunities of exploiting these structures for the discovery of new anti-TB drugs are emphasized.Expert opinion: The drug discovery efforts targeting the ETC pathway have led to the FDA approval of bedaquiline, a FOF1-ATP synthase inhibitor, and the discovery of Q203, a clinical candidate drug targeting the mycobacterial cytochrome bcc-aa3 supercomplex. Moreover, clofazimine, a proposed prodrug competing with menaquinone for its reduction by mycobacterial NADH dehydrogenase 2, has been repurposed for TB treatment. Recently available structures of the mycobacterial ATP synthase C9 rotary ring and the cytochrome bcc-aa3 supercomplex represent further opportunities for the structure-based drug design (SBDD) of the next-generation of inhibitors against Mycobacterium tuberculosis.

Use of Dexmedetomidine and Esmolol for Hypotension in Lumbar Spine Surgery.

BACKGROUND: The importance of decreasing bleeding in spine surgery is not only important to maintain the patient's hemodynamic balance but also allow a better view of the surgical field. OBJECTIVES: The current study aimed to compare dexmedetomidine and Esmolol™ as agents to induce hypotension in lumbar spine surgeries. PATIENTS AND METHODS: A total of 50 patients aged 20 to 65 years belonging to the American society of anaesthesiologist (ASA) class I - II scheduled for decompression and fixation of the lumbar spine were included and divided into two groups namely, Group I, who received Esmolol and group II, who received dexmedetomidine, intravenously. The patients were compared for intraoperative hemodynamic parameters, estimated blood loss, operation time, intraoperative analgesic (fentanyl) consumption, and total fall in haemoglobin (Hb) during the perioperative period. RESULTS: The study results showed that dexmedetomidine had lower (100.8 µg) fentanyl and sevoflurane consumption (1.2%), and less blood loss (278 mL) in comparison to the Esmolol group. CONCLUSIONS: Both dexmedetomidine and Esmolol can be used as agents to control hypotension in patients undergoing lumbar spine decompression and fixation surgery; the dexmedetomidine group, however, was associated with better intraoperative hemodynamic stability and reduced intraoperative analgesic and volatile anaesthetic requirement.

Multidrug-resistant and extensively drug resistant tuberculosis in Kashmir, India.

BACKGROUND: To study the profile of multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) in tertiary care hospital setting, representing almost the whole affected population in Kashmir valley of India. METHODOLOGY: A total of 910 cases of pulmonary tuberculosis were enrolled over four years. Among these, cases of MDR-TB and XDR-TB were meticulously studied for drug susceptibility, treatment, adverse effects profile and overall survival. RESULTS: Fifty-two (5.7%) cases of MDR-TB were identified, among which eight (15.3%) were diagnosed as XDR-TB on the basis of drug susceptibility testing, using the prescribed definition. The cases were sensitive to 2, 3, 4, 5 and more than 5 drugs in almost equal proportions. Thirty-seven (71.1%) cases were successfully cured; eleven (21.1%) patients died; and only four (7.6%) cases defaulted, indicating overall satisfactory adherence to treatment. CONCLUSION: For effective treatment of MDR-TB and XDR-TB, early case detection, improved laboratory facilities, availability of appropriate treatment regimens, and financial assistance in resource-limited settings through effective political intervention are necessary for better patient adherence and overall cure.